ArticleGenome biology2007
Identification of novel stem cell markers using gap analysis of gene expression data.
Article in Genome biology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Longitudinal single-cell RNA-seq of hESCs-derived retinal organoids.Science China. Life sciences · 2021Article
- A comparison of performance of plant miRNA target prediction tools and the characterization of features for genome-wide target prediction.BMC genomics · 2014Article
- CellFinder: a cell data repository.Nucleic acids research · 2014Article
- Deeply dissecting stemness: making sense to non-coding RNAs in stem cells.Stem cell reviews and reports · 2012Review
- Preimplantation development regulatory pathway construction through a text-mining approach.BMC genomics · 2011Article
- Recent developments in StemBase: a tool to study gene expression in human and murine stem cells.BMC research notes · 2009Article
- Gene expression in murine mammary epithelial stem cell-like cells shows similarities to human breast cancer gene expression.Breast cancer research : BCR · 2009Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We describe a method for detecting marker genes in large heterogeneous collections of gene expression data. Markers are identified and characterized by the existence of demarcations in their expression values across the whole dataset, which suggest the presence of groupings of samples. We apply this method to DNA microarray data generated from 83 mouse stem cell related samples and describe 426 selected markers associated with differentiation to establish principles of stem cell evolution.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.